title: Measuring employment precariousness in the European Working Conditions Survey: the social distribution in Europe.
abstract: BACKGROUND
  Precarious employment is becoming an increasingly important social determinant of health inequalities among workers. The way in which contemporary employment arrangements and their health consequences are addressed in empirical research is mostly based on the contract-related or employment instability dimension. A broader conceptual approach including various important characteristics of the degrading of employment conditions and relations is needed.
  
  
  OBJECTIVE
  The general objective of this paper is to empirically test a new multidimensional construct for measuring precarious employment in an existing database. Special focus is on the social distribution of precarious employment.
  
  
  METHODS
  A subsample of 21,415 participants in the EU-27 from the Fourth European Working Conditions Survey-2005 was analysed. A cross-sectional study of the social distribution of precarious employment was conducted through the analysis of proportional differences according to gender, social class and credentials for the European Union as a whole and within each country. The 8 dimensions of the employment precariousness construct were represented by 11 indicators.
  
  
  RESULTS
  In general, women, workers without supervisory authority, those with fewer credentials, and those living in Eastern and Southern European countries suffer the highest levels of precarious employment. Exceptionally, men, workers with supervisory authority and those with the highest credentials suffer the highest levels of long working hours, schedule unpredictability and uncompensated flexible working times.
  
  
  CONCLUSIONS
  This article offers the first validation for an innovative multidimensional conceptualisation of employment precariousness applied to the analysis of existing survey data, showing the unequal distribution of precarious employment across the European labour force. This set of indicators can be useful for monitoring precarious employment.
authors.forename: Vanessa
authors.initials: V
authors.lastname: Puig-Barrachina
authors.forename: Christophe
authors.initials: C
authors.lastname: Vanroelen
authors.forename: Alejandra
authors.initials: A
authors.lastname: Vives
authors.forename: José Miguel
authors.initials: JM
authors.lastname: Martínez
authors.forename: Carles
authors.initials: C
authors.lastname: Muntaner
authors.forename: Katia
authors.initials: K
authors.lastname: Levecque
authors.forename: Joan
authors.initials: J
authors.lastname: Benach
authors.forename: Fred
authors.initials: F
authors.lastname: Louckx
mesh_terms: D000293:Adolescent; D000328:Adult; D003098:Collective Bargaining; D004651:Employment / Q000523:psychology / Q000706:statistics & numerical data* / Q000639:trends; D005060:Europe; D005260:Female; D054624:Health Status Disparities; D006806:Human Rights; D006801:Humans; D007182:Income / Q000706:statistics & numerical data; D007318:Inservice Training; D008297:Male; D008875:Middle Aged; D012307:Risk Factors; D012737:Sex Factors; D064890:Social Determinants of Health; D012959:Socioeconomic Factors; D011795:Surveys and Questionnaires; D035501:Uncertainty; D016526:Workload